Prediction of Credit-Card Defaulters: A Comparative Study on Performance of Classifiers
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Foundation of Computer Science
Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. A Provisional Study of Data Mining Classification Algorithms in Predicting Credit Card Defaulters Using Weka Tools;2023 IEEE 8th International Conference on Recent Advances and Innovations in Engineering (ICRAIE);2023-12-02
2. Prediction of credit card defaults through data analysis and machine learning techniques;Materials Today: Proceedings;2022
3. Predicting the loan risk towards new customer applying data mining using nearest neighbor algorithm;IOP Conference Series: Materials Science and Engineering;2020-04-01
4. Performance Comparison of Data Mining Algorithm to Predict Approval of Credit Card;SinkrOn;2019-10-05
5. Default avoidance on credit card portfolios using accounting, demographical and exploratory factors: decision making based on machine learning (ML) techniques;Annals of Operations Research;2019-03-15
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